Can We See Sycophancy Before It Appears?
A Longitudinal Test of Interaction-Level Leading Indicators
In dialogue with “Emotion Concepts and their Function in a Large Language Model”
Sofroniew, Kauvar, Saunders, et al. (Anthropic, 2026)
Rob Panico
The Mountain Eagle
Abstract
Sofroniew et al. show that large language models contain internal representations associated with emotion concepts and that manipulating those representations can causally affect model behavior, including behaviors relevant to alignment.
That gives us an internal view of something important.
This paper asks whether there is a useful external view as well.
Specifically: can measurable changes in the structure of an interaction predict later behavioral degradation before the problematic output becomes obvious?
I propose a small set of longitudinal measurements covering continuity, reversibility, contradiction and compression fidelity, combined into a provisional Resonance Integrity Score (RIS). The purpose of RIS is not to measure consciousness, emotion, identity or some hidden quantity called coherence. It is an instrument candidate.
The central prediction is narrow: declining interaction-level measurements will predict later sycophantic behavior or loss of carry-forward value better than simpler baselines such as sentiment, agreement and turn length.
If they do, longitudinal interaction contains useful alignment information that isn't visible in the current output alone.
If they don't, the framework needs revision.
1. The internal result and the external question
Sofroniew et al. give us evidence that concepts associated with emotion are represented internally in language models and can causally affect what those models subsequently produce. Their work is careful not to turn this into a claim about subjective experience. “Functional emotion” describes something the model is doing, not evidence that the model feels what a person would feel.
That distinction is useful.
The reported relationship with behaviors such as sycophancy creates another question that mechanistic interpretability doesn't need to answer in order to do its job.
What was happening in the interaction before the problematic behavior appeared?
An internal representation can help explain why a particular response became more likely. An interaction-level analysis asks whether anything observable across previous turns indicated that the conditions surrounding that response were changing.
These are different observer positions.
Neither needs to replace the other.
If the internal and external measurements eventually correlate, we learn something interesting. If they don't, we learn something interesting too.
The first task is simply to determine whether the external signal exists.
2. Sycophancy as the first test case
I've previously described sycophancy as Opposition collapse.
I now think that language gets ahead of the evidence.
There is a useful observation underneath it. A conversation that becomes increasingly confirmatory may lose opportunities for contradiction to modify what happens next. The model can continue producing nuanced, fluent and apparently reflective responses while becoming less willing to challenge assumptions already established in the interaction.
That pattern could precede sycophancy.
It could also merely accompany it.
Or I could be imposing a structure on conversations that isn't predictively useful at all.
We can test the difference.
Instead of defining sycophancy as Opposition collapse, we can ask whether interactions that later produce sycophantic behavior show measurable changes beforehand. Do contradiction-bearing turns become less common? Does the conversation become harder to reopen? Are previous claims carried forward less accurately? Does apparent continuity remain high while opportunities for correction decline?
Those are observable questions.
They also leave room for the answer to be no.
3. What should we measure?
The current